{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 柱状图\n",
    ">应用于比较分类变量的数值，例如可以用于展示衣服裤子鞋子等商品的销售量。\n",
    "\n",
    "## 主要参数介绍：\n",
    "bar(left, height, width=0.8, bottom=None, **kwargs)\n",
    "1. left为和分类数量一致的数值序列，序列里的数值数量决定了柱子的个数，数值大小决定了距离0点的位置\n",
    "2. height为分类变量的数值大小，决定了柱子的高度\n",
    "3. width决定了柱子的宽度，仅代表形状宽度而已\n",
    "4. bottom决定了柱子距离x轴的高度，默认为None，即表示与x轴距离为0\n",
    "\n",
    "事实上，left，height，width，bottom这四个参数确定了柱体的位置和大小。默认情况下，left为柱体的居中位置（可以通过align参数来改变left值的含义）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 正常显示中文标签\n",
    "plt.rcParams['font.sans-serif']=['SimHei']\n",
    "# 用来正常显示负号\n",
    "plt.rcParams['axes.unicode_minus']=False\n",
    "\n",
    "plt.rcParams['axes.labelsize']=16\n",
    "plt.rcParams['xtick.labelsize']=14\n",
    "plt.rcParams['ytick.labelsize']=14\n",
    "plt.rcParams['legend.fontsize']=12\n",
    "plt.rcParams['figure.figsize']=[16,6]\n",
    "# 使用样式\n",
    "plt.style.use(\"ggplot\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "label = [\"a\",\"b\",\"c\",\"d\",\"e\"]\n",
    "x = [0,1,2,3,4]\n",
    "y = [30,20,15,25,10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## width决定了柱子的宽度，仅代表形状宽度而已，默认为0.8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "\n",
    "# 生成第一个子图在1行2列第一列位置\n",
    "ax1 = fig.add_subplot(121)\n",
    "\n",
    "# 生成第二子图在1行2列第二列位置\n",
    "ax2 = fig.add_subplot(122)\n",
    "\n",
    "# 绘图并设置柱子宽度0.5\n",
    "ax1.bar(x, y, width=0.5)\n",
    "\n",
    "# 绘图默认柱子宽度0.8\n",
    "ax2.bar(x, y)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 设置x轴刻度（tick_label）用 label = [\"a\",\"b\",\"c\",\"d\",\"e\"] 显示"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "\n",
    "# 生成第一个子图在1行2列第一列位置\n",
    "ax1 = fig.add_subplot(121)\n",
    "\n",
    "# 生成第二子图在1行2列第二列位置\n",
    "ax2 = fig.add_subplot(122)\n",
    "\n",
    "# 绘图并设置柱子宽度0.5\n",
    "ax1.bar(x, y, width=0.5)\n",
    "\n",
    "# 绘图默认柱子宽度0.8,设置x轴刻度（tick_label）用 label = [\"a\",\"b\",\"c\",\"d\",\"e\"] 显示\n",
    "ax2.bar(x, y,tick_label=label)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## bottom决定了柱子距离x轴的高度，默认为None，即表示与x轴距离为0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots(figsize=(8,5),dpi=80)\n",
    "\n",
    "# 设置第一个柱子离x轴 为5 ，第二、三、五个柱子不变，第四个柱子离x轴 为8 \n",
    "ax.bar(x,y,width=0.3,bottom=[5,0,0,8,0])\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 设置柱体颜色\n",
    "通过 facecolor(或fc) 关键字参数可以设置柱体颜色\n",
    "\n",
    "通过 color 关键字参数 可以一次性设置多个颜色"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "\n",
    "# 生成第一个子图在1行2列第一列位置\n",
    "ax1 = fig.add_subplot(121)\n",
    "\n",
    "# 生成第二子图在1行2列第二列位置\n",
    "ax2 = fig.add_subplot(122)\n",
    "\n",
    "ax1.bar(x, y, fc='c')\n",
    "\n",
    "ax2.bar(x, y,color=['r', 'g', 'b']) # 或者color='rgb' , color='#FFE4C4'\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 设置柱体描边\n",
    "\n",
    "相关的关键字参数为：\n",
    "\n",
    "+ edgecolor 或 ec 描边颜色\n",
    "+ linestyle 或 ls 描边样式\n",
    "+ linewidth 或 lw 描边宽度"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# edgecolor 或 ec 描边颜色为（cyan），linestyle 或 ls 描边样式 （-.）， linewidth 或 lw 描边宽度（5），柱子颜色（#EECFA1）\n",
    "plt.bar(x, y, ec='c', ls='-.', lw=5,color='#EECFA1')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 设置柱体描边填充\n",
    "hatch 关键字可用来设置填充样式，可取值为： / , \\ , | , - , + , x , o , O , . , * 。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(x, y, ec='c', ls='-.', lw=5,color='#EEDC82',hatch='*')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 其他柱状图类型"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### （1）堆积柱状图\n",
    "\n",
    "通过 bottom 参数，可以绘制堆叠柱状图。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 960x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#显示中文字体为SimHei\n",
    "plt.rcParams[\"font.sans-serif\"]=[\"SimHei\"]\n",
    "\n",
    "sale8 = [10,20,30,15,18]\n",
    "sale9 = [10,12,24,32,8]\n",
    "\n",
    "# x轴的刻度为1-5号衣服\n",
    "labels = [\"{}号衣服\".format(i) for i in range(1,6)]\n",
    "\n",
    "fig,ax = plt.subplots(figsize=(12,6),dpi=80)\n",
    "\n",
    "\n",
    "ax.bar(range(len(sale8)),sale8,tick_label=labels,label=\"8月\")\n",
    "\n",
    "# 九月的bottom是sale8，也就是八月，所以九月在上边\n",
    "ax.bar(range(len(sale9)),sale9,bottom=sale8,tick_label=labels,label=\"9月\")\n",
    "ax.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## （2）并列柱状图\n",
    "\n",
    "绘制并列柱状图与堆叠柱状图类似，都是绘制多组柱体，只需要控制好每组柱体的位置和大小即可。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "#显示中文字体为SimHei\n",
    "plt.rcParams['font.sans-serif']=['SimHei']\n",
    "\n",
    "sale8 = [5,20,15,25,10]\n",
    "sale9 = [10,15,25,30,5]\n",
    "\n",
    "# x轴的刻度为1-5号衣服\n",
    "labels = [\"{}号衣服\".format(i) for i in range(1,6)]\n",
    "\n",
    "fig,ax = plt.subplots(figsize=(8,5),dpi=80)\n",
    "width_1 = 0.4\n",
    "\n",
    "ax.bar(np.arange(len(sale8)),sale8,width=width_1,tick_label=labels,label = \"8月\")\n",
    "\n",
    "ax.bar(np.arange(len(sale9))+width_1,sale9,width=width_1,tick_label=labels,label=\"9月\")\n",
    "\n",
    "ax.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 条形图\n",
    "使用 barh 方法绘制条形图\n",
    "\n",
    "### plt.barh 方法的签名为：\n",
    ">barh(bottom, width, height=0.8, left=None, **kwargs)\n",
    "### 可以看到与 plt.bar 方法类似。所以堆积条形图和并列条形图的画法与前面类似。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.barh(x, y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 正负条形图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "x = np.array([5, 20, 15, 25, 10])\n",
    "y = np.array([11, 15, 22, 14, 5])\n",
    "\n",
    "plt.barh(range(len(x)), x)\n",
    "plt.barh(range(len(y)), -y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 案例一：同一本书不同平台最低价比较\n",
    "很多人在买一本书的时候，都比较喜欢货比三家，例如《python数据分析实战》在亚马逊、当当网、中国图书网、京东和天猫的最低价格分别为39.5、39.9、45.4、38.9、33.34。针对这个数据，我们也可以通过条形图来完成，这里使用水平条形图来显示："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 正常显示中文标签\n",
    "plt.rcParams['font.sans-serif']=['SimHei']\n",
    "# 用来正常显示负号\n",
    "plt.rcParams['axes.unicode_minus']=False\n",
    "\n",
    "plt.rcParams['axes.labelsize']=16\n",
    "plt.rcParams['xtick.labelsize']=14\n",
    "plt.rcParams['ytick.labelsize']=14\n",
    "plt.rcParams['legend.fontsize']=12\n",
    "plt.rcParams['figure.figsize']=[15,15]\n",
    "plt.style.use(\"ggplot\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 39.5\n",
      "1 39.9\n",
      "2 45.4\n",
      "3 38.9\n",
      "4 33.34\n"
     ]
    }
   ],
   "source": [
    "price = [39.5,39.9,45.4,38.9,33.34]\n",
    "for x,y in enumerate(price):\n",
    "    print(x,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 960x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots(figsize=(12,5),dpi=80)\n",
    "\n",
    "x = range(len(price))\n",
    "# 添加刻度标签\n",
    "labels = np.array(['亚马逊','当当网','中国图书网','京东','天猫'])\n",
    "#在子图对象上画条形图，并添加x轴标签，图形的主标题\n",
    "ax.barh(x,price,tick_label=labels,alpha = 0.8)\n",
    "\n",
    "ax.set_xlabel('价格',color='k')\n",
    "ax.set_title('不同平台书的最低价比较')\n",
    "\n",
    "# 设置Y轴的刻度范围\n",
    "ax.set_xlim([32,47])\n",
    "\n",
    "# 为每个条形图添加数值标签\n",
    "for x,y in enumerate(price):\n",
    "    ax.text(y+0.2,x,y,va='center',fontsize=14)\n",
    "    \n",
    "# 显示图形   \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 代码解读\n",
    "水平条形图的绘制与垂直条形图的绘制步骤一致，只是调用了barh函数来完成。需要注意的是，条形图的数值标签设置有一些不一样，需要将标签垂直居中显示，使用va参数即可。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 案例二：胡润财富榜：亿万资产超高净值家庭数\n",
    "利用水平交错条形图对比2016年和2017年亿万资产超高净值家庭数（top5），其数据如下："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 正常显示中文标签\n",
    "plt.rcParams['font.sans-serif']=['SimHei']\n",
    "# 用来正常显示负号\n",
    "plt.rcParams['axes.unicode_minus']=False\n",
    "\n",
    "plt.rcParams['axes.labelsize']=16\n",
    "plt.rcParams['xtick.labelsize']=14\n",
    "plt.rcParams['ytick.labelsize']=14\n",
    "plt.rcParams['legend.fontsize']=16\n",
    "plt.rcParams['figure.figsize']=[12,10]\n",
    "plt.style.use(\"ggplot\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 构建数据\n",
    "Y2016 = [15600,12700,11300,4270,3620]\n",
    "Y2017 = [17400,14800,12000,5200,4020]\n",
    "labels = ['北京','上海','香港','深圳','广州']\n",
    "bar_width = 0.35\n",
    "x = np.arange(len(Y2016))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "\n",
    "# 绘图\n",
    "ax.bar(x,Y2016,label='Y2016',width=bar_width)\n",
    "ax.bar(x+bar_width,Y2017,label='Y2017',width=bar_width)\n",
    "# 添加轴标签\n",
    "ax.set_xlabel('Top5城市')\n",
    "ax.set_ylabel('家庭数量')\n",
    "# 添加标题\n",
    "ax.set_title('亿万财富家庭数Top5城市分布',fontsize=16)\n",
    "# 添加刻度标签\n",
    "plt.xticks(x+bar_width,labels)\n",
    "# 设置Y轴的刻度范围\n",
    "plt.ylim([2500, 19000])\n",
    "\n",
    "# 为每个条形图添加数值标签\n",
    "for x2016,y2016 in enumerate(Y2016):\n",
    "    plt.text(x2016, y2016+200, y2016,ha='center',fontsize=16)\n",
    "\n",
    "for x2017,y2017 in enumerate(Y2017):\n",
    "    plt.text(x2017+0.35,y2017+200,y2017,ha='center',fontsize=16)\n",
    "    \n",
    "# 显示图例\n",
    "ax.legend()\n",
    "# 显示图形\n",
    "plt.show()"
   ]
  }
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